Finger Nail Plate Classification for Transient Biometric Identification
Keywords:
Texture feature extraction, neural network, LBP, matching, preprocessing, SIFTAbstract
Transient biometrics using finger nail plate is a new for biometric identification and verification. According to traditional research biometric system concentrates on biometric characteristics which are constant i.e. for a long time or permanent. Transient means “short time” (not permanent). Texture features extracted with the help of LBP (Local Binary Pattern) and scale invariant feature transform(SIFT) from finger nail plate and after all the features classified with the help of the neural network. Previous work is done using fusion work of LBP, Adaboost, brisk and PCA. Proposed methodology uses finger nail plate image data set from the website TBND group. The work is carried out using finger nail images in Matlab environment.
References
[1]. R. V. Hogg, A. T. C. (1965). Introduction to Mathematical Statistics. New York: Macmillan, IEEE. [2]. D. N. Graham, (1967). Image transmission by two-dimensional contour coding. vol. 55, Mar. pp. 336-346, IEEE. [3]. Robert M. Harlick, K. S. (1973). Textural Feature for Image Classification. IEEE [4]. A.H. Mir (1995). Texture analysis of CT images, Engineering in Medicine and Biology November-December IEEE. [5]. T. Ojala, M. P. (1997). Gray Scale and Rotation Invariant Classification with Local Binary Pattern, [6]. B. Verma, S. K. (2001). Texture Feature Extraction and Classification, CAIP, LNCS 2124, 228–235, 2001. Springer. [7]. Jane You, Wenxin Li, D. Z. (2002). Hierarichal Palmprint Identification Via Multiple Feature Extraction. Elsevier. [8]. R.M. Ayala, M. M. (2002). Evaluation Methodology for Classification Process of Digital Images. IEEE. [9]. T. Ahonen. (2006). Face description with local binary patterns: application to face recognition”. transactions on pattern analysis and machine intelligence, 28(12):2037–41, Dec. IEEE. [10]. Ryszard S. Choras, (2007). Image feature extraction techniques and their applications of CBIR and BIO metrics system, international journal of biology and biomedical engineering. [11]. Namita Aggarwal (2009). First and Second Order Statistics Features for Classification of Magnetic Resonance Brain Images. Journal of Signal and Information Processing, 2012, 3, 146-153.Volume 9, August. [12]. P. Babaghorbani et.al. (2010). Sonography Images for Breast Cancer Texture classification in Diagnosis of Malignant or Benign Tumors”. 978-1-4244-47. IEEE. [13]. C. Rathgeb, (2011). A survey on biometric cryptosystems and cancelable biometrics. EURASIP Journal on Information Security. [14]. Leutenegger (2011). Binary robust invariant scalable key points in computer. IEEE Int. Conf.0,2548– 2555. [15]. S. Garg, A. Kumar et.al. (2012). Biometric authentication using finger nail surface, In 12th International Conference on Intelligent Systems Design and Applications (ISDA), pages 497–502. IEEE. [16]. Rohit Verma, et.al. (2012). A-Survey of Feature Extraction and Classification Techniques in OCR Systems, International Journal of Computer Applications & Information Technology Vol. I, Issue III, November (ISSN: 2278-7720). [17]. Igor Barros Barbosa et.al. (2013). Transient Biometrics using Finger Nail plate” 2013 [18]. Amioy Kumar et.al. (2013). Biometric Authentication Using Finger Nail Plates” Expert Systems with Applications. [19]. Sashi Kumar Patra (2013). Texture Analysis Using Statistical and Structural Approaches, International Journal of Latest Trends in Engineering and Technology (IJLTET) Vol. 3 Issue 1 September. [20]. Arati Shitole et.al. (2013). Transient Authentication, International Journal of Research in Computer and Communication Technology, Vol 2, Issue 2. [21]. Hardik Pandit et.al. (2013). A System for Nail Color Analysis in Healthcare, IEEE. [22]. Arun Verma, (2014). Content based image retrieval using color, texture and shape Feature International Journal of Computer Science and Software Engineering, IEEE. [23]. Gaurav Kumar (2014). A detailed review of feature extraction in image processing system, Fourth International Conference on advance computing and communication technologies. [24]. Vipara sharma (2015). System for disease detection by analyzing finger nail color and texture”, journal of advance engineering research and science. [25]. Loyce Selwyn Pinto et.al. (2016). Crop Disease Classification using Texture Analysis. International Conference On Recent Trends in Electronics Information Communication Technology. IEEE. [26]. Sourajit Das et.al. (2016). Texture Classification using Combination of LBP and GLRLM Features along with KNN and Multiclass SVM Classification”. IEEE 2nd International Conference on Communication, Control and Intelligent Systems (CCIS). IEEE. [27]. Satish Kumar et.al. (2016). Biometric Authentication using finger nails. IEEE. [28]. Dr. Tripty Singh (2016). Design of A Dual Biometric Authentication System. International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). [29]. Sakshi Sharma et.al. (2016). Recent Advancement of LBP Techniques: A Survey. International Conference on Computing, Communication and Automation (ICCCA). [30]. Ranjit Biswas et.al. (2016). Mammogram Classification using Gray-Level Co-occurrence Matrix for Diagnosis of Breast Cancer, International Conference on Micro-Electronics and Telecommunication Engineering. ICMETE. [31]. Renu Bala, "Survey on Texture Feature Extraction Methods." International Journal of Engineering Science and Computing, ISSN 2250-1371, volume 7, issue no. 4, April 2017.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT
This work is licensed under a Creative Commons Attribution 4.0 International License.